A combination of electrophysiological experiments and computational modeling has led to the hypothesis that acetylcholine may set the appropriate dynamics for learning in the cortex, while removal of cholinergic modulation may set the appropriate dynamics for recall. In this application, we propose to test this hypothesis using the techniques of brain slice physiology. Predictions have been generated using simplified representations of cortical structures as systems of differential equations. In these simulations, feedback regulation of cortical cholinergic modulation allows cortical regions to set their own state of learning or recall dependent upon the familiarity of the incoming information. The memory function of the network is evaluated using a performance measure based on normalized dot products. This leads to predictions about the parameters of cholinergic modulation which give the most effective memory function. Biophysical network simulations will be used to further analyze the validity of these predictions. Experimental data about the relative amplitude of cholinergic effects on cortical parameters will be compared with computational predictions. Experimental work will determine the relative amplitude and dose response curves for cholinergic suppression of neuronal adaptation and afterhyperpolarization currents, the cholinergic suppression of inhibitory synaptic transmission, the cholinergic enhancement of synaptic modification, and the cholinergic suppression of synaptic transmission within the hippocampal formation. In addition, the possibility that GABAergic innervation arising from the basal forebrain selectively suppresses synaptic transmission in a manner similar to acetylcholine will be tested experimentally. Understanding the feedback regulation of cortical cholinergic innervation may shed light on the basis for degeneration of this cholinergic innervation in Alzheimer's disease. In addition, this work will increase understanding of the general role of neuromodulators in cortical function, since other neuromodulators influence many of the same physiological parameters. This may suggest new strategies for the use of drugs in the treatment of psychiatric disorders, since many of these drugs have a strong influence on neuromodulatory systems.